著名跨国公司的6 Sigma BB黑带培训资料-  TRW_Booster_WK2_10_Reliability_0704_V3.pptVIP

Reliability Overview of this module Basic concepts Parametric Analysis Non-parametric Analysis Redundancy Reliability Basic Concepts What is reliability? Products and systems are expected to function at the point of delivery and for a certain time. Sometimes there are contractual terms determining the time a system is expected to function without a limitation, e.g. warranty times. Reliability is “Quality over Time”. So reliability has to be developed into a product or system. Common hazard function: The “Bathtub” Curve Who’s in charge of reliability? Reliability Roadmap Basic Concepts Definitions Reliability is the probability of a product (or system) performing its purpose satisfactorily for a specified time period given specified operating conditions. Probability ranges from 0 (or 0%) - complete unreliability to 1 (or 100%) - complete reliability. E.g. - if we say that a unit is 70% reliable at 2000 hours, (in shorthand; R (2000) = 0.70 ) we mean that 70% of units will last at least 2000 hours before failure. Failure percentage F is (100 - R) , where R is the Reliability percentage (eg 30% of units will fail before 2000 hours.) Basic Concepts, cont. Knowing the underlying failure distribution (e.g. Weibull form illustrated here - see Appendix), we can estimate the reliability (or failure percentage) at any age. At 0 hours the reliability is 100%. At 2000 hours (after a cumulative 30% failures), the reliability is 70%. Note that the reliability statement is x% reliability at xx hours. We can also determine: the Survival Function or Lifetime to Failure the Hazard Function or Hazard Rate (Mortality Rate) Basic Concepts, example From the table: at 10,000 hours, the reliability is 94 % at 40,000 hours, the reliability is 14 % Example – Failures over Time Example – Survival Function Example – Hazard Rate Example – Summary Parametric vs. Non-parametric Analysis In the example so far, we have relied on visual interpretation of the graphs. We hav